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Empirical Study on the Grain Output Based on Regression Analysis

  • Jiahao Xu
  • , Sai Tang*
  • , Pengyan Li
  • , Hexu Zhang
  • *Corresponding author for this work
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Based on a literature review of influencing factors and forecasting methods for grain production, the empirical analysis of the influencing factors of China's grain output is performed using the full subset regression method, the ridge regression method, and the LASSO regression method. The results show that (1) the increase in the sown area of grain crops is the main reason for the increase in grain output, (2) the use of agricultural fertilizers and the increase in rural electricity consumption are the driving factors for the increase in grain output, (3) the impact of total power of agricultural machinery is limited, and (4) natural disasters have a certain negative impact on food production.

Original languageEnglish
Article number2567790
JournalJournal of Sensors
Volume2022
DOIs
StatePublished - 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  2. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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